151 lines
4.8 KiB
Python
151 lines
4.8 KiB
Python
"""端到端验证：process_image 输出 vs 实际写入 docx 的图片字节。
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目的:
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用户反馈"从文档复制出来的图底部有 1/4 空白"，但独立测试 process_image
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输出已是紧致裁剪。本脚本走完整 sign_word 链路，把生成的 docx 解开来看
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word/media/ 下真实的图片字节，对比 process_image 的输出，定位空白来源:
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- 若字节完全一致 → 空白来自 Word 段落渲染（行高/对齐），不是图片本身
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- 若字节不一致 → 我们的链路在某个环节给图片加了 padding，需进一步定位
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使用:
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python image_test/e2e_test.py
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"""
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import io
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import sys
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import zipfile
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from pathlib import Path
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BASE_DIR = Path(__file__).resolve().parent
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PROJECT_ROOT = BASE_DIR.parent
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INPUT_IMAGE = BASE_DIR / "input" / "test1.jpg"
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OUT_DIR = BASE_DIR / "output" / "e2e"
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DOCX_OUT = OUT_DIR / "signed.docx"
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def _ensure_project_on_path():
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if str(PROJECT_ROOT) not in sys.path:
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sys.path.insert(0, str(PROJECT_ROOT))
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def _make_test_docx(path):
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"""构造一份带 SET USER_test 域代码的 docx，正文段落使用偏大行高。
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段落行高 2cm（lineRule=exact），模拟用户文档里的固定行高场景。
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"""
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from docx import Document
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from docx.shared import Cm, Pt
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from docx.enum.text import WD_LINE_SPACING
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from lib import field_codes
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doc = Document()
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p = doc.add_paragraph()
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p.paragraph_format.line_spacing_rule = WD_LINE_SPACING.EXACTLY
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p.paragraph_format.line_spacing = Cm(2.0)
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p.add_run("正文前 ")
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runs = field_codes.build_set_field_runs("test")
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for r in runs:
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p._element.append(r)
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p.add_run(" 正文中 ")
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p.add_run("正文后")
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doc.save(str(path))
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def _image_stats(data):
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from PIL import Image, ImageChops
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img = Image.open(io.BytesIO(data))
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if img.mode != 'RGBA':
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img = img.convert('RGBA')
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r, g, b, a = img.split()
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luma = Image.merge('RGB', (r, g, b)).convert('L')
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alpha_mask = a.point(lambda p: 255 if p > 30 else 0)
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luma_mask = luma.point(lambda p: 255 if p < 210 else 0)
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combined = ImageChops.darker(alpha_mask, luma_mask)
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total = img.size[0] * img.size[1] or 1
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return {
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'size': img.size,
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'mode': img.mode,
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'content_pct': 100.0 * sum(combined.histogram()[1:]) / total,
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'alpha_pct': 100.0 * sum(alpha_mask.histogram()[1:]) / total,
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'bbox': combined.getbbox(),
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'sha256': __import__('hashlib').sha256(data).hexdigest()[:16],
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}
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def main():
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_ensure_project_on_path()
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if not INPUT_IMAGE.exists():
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print(f"测试图片不存在: {INPUT_IMAGE}")
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sys.exit(1)
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OUT_DIR.mkdir(parents=True, exist_ok=True)
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src_docx = OUT_DIR / "input.docx"
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_make_test_docx(src_docx)
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with open(src_docx, 'rb') as f:
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docx_data = f.read()
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with open(INPUT_IMAGE, 'rb') as f:
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image_bytes = f.read()
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from lib.image_processor import process_image
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from lib.word_signer import sign_word
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processed = process_image(
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image_bytes, is_signature=True,
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noise_level=0, rotate_min=0, rotate_max=0,
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log_source='e2e测试',
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)
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params = {
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'docx_name': 'input.docx',
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'match_mode': 'upload',
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'stamps': [{
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'marker': 'USER_test',
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'image_base64': __import__('base64').b64encode(image_bytes).decode(),
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'image_filename': 'test1.jpg',
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'is_signature': True,
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}],
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'use_global_height': True,
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'height': 2.5,
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}
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result, err = sign_word(docx_data, params, log_source='e2e测试', trace_id='e2e')
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if err:
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print(f"sign_word 失败: {err}")
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sys.exit(1)
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with open(DOCX_OUT, 'wb') as f:
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f.write(result['data'])
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print(f"已生成: {DOCX_OUT}")
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print(f"warnings: {result.get('warnings', [])}")
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print(f"success_count: {result.get('success_count', 0)}")
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print()
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print("=== process_image 直出 ===")
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s1 = _image_stats(processed)
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print(f" 尺寸={s1['size']} 内容={s1['content_pct']:.1f}% "
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f"alpha={s1['alpha_pct']:.1f}% bbox={s1['bbox']} sha={s1['sha256']}")
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print()
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print("=== docx 内 word/media/ 实际图片 ===")
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with zipfile.ZipFile(DOCX_OUT, 'r') as z:
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medias = sorted(n for n in z.namelist() if n.startswith('word/media/'))
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if not medias:
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print(" 未找到任何图片！")
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return
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for name in medias:
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data = z.read(name)
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s2 = _image_stats(data)
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same = "一致" if data == processed else "不一致"
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print(f" [{name}] 尺寸={s2['size']} 内容={s2['content_pct']:.1f}% "
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f"alpha={s2['alpha_pct']:.1f}% bbox={s2['bbox']} sha={s2['sha256']} 字节={same}")
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print(f" 原始 {len(processed)} bytes vs docx {len(data)} bytes")
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if __name__ == '__main__':
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main()
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